Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A system for communicating data in a process control system of a process plant, the system comprising: a first device that: is included in the process control system and is operable, during run-time of the process plant, to control a process in the process plant to thereby generate a physical material or product, is further operable during run-time of the process plant to transmit a data stream, and is configured to (i) store a set of data for transmitting as the data stream and store a set of metadata descriptive of the data stream, the set of data generated by the first device and including a set of values of one or more parameters whose respective values vary as a result of the first device operating to control the process, and (ii) transmit all of the set of metadata to a second device prior to transmitting the data stream to the second device, wherein the first device is one of (i) a controller communicatively connected to one or more field devices disposed in the process plant, the controller configured to send control signals to the one or more field devices to thereby control the process during run-time in the process plant, or (ii) one of the one or more field devices, and wherein the set of metadata comprises (i) respective descriptions of types of data included in the data stream and (ii) a description of a format of the data stream, and includes respective identifiers of one or more portions of a configuration of the first device, the one or more portions of the configuration of the first device including at least one of: a control module that is downloaded into the controller and executable during run-time to generate and send the control signals to the one or more field devices to thereby control the process in the process plant, a function block included in the control module, a process parameter, a unit corresponding to the first device, another device that accesses or acts on at least one of a process input or a process output of the first device, an event, or an alarm; the second device, the second device being operable to receive the data stream and configured to receive the set of metadata, wherein: the first device is further configured to transmit the data stream to the second device, and the second device is further configured to receive the data stream from the first device after receiving all of the set of metadata, and parse the received data stream according to the set of metadata.
This system enables efficient data communication in a process control system within a process plant. The system addresses the challenge of transmitting and interpreting data streams generated by devices that control industrial processes, ensuring that the data is properly understood by receiving devices. The system includes a first device, which can be either a controller or a field device, responsible for controlling a process in the plant to produce a physical material or product. During operation, this device generates a data stream containing parameter values that vary as the process is controlled. The device also stores metadata describing the data stream, including the types of data, the data format, and identifiers for portions of its configuration, such as control modules, function blocks, process parameters, units, related devices, events, or alarms. Before transmitting the data stream, the first device sends all metadata to a second device, which receives and parses the data stream according to the metadata. This ensures that the second device can accurately interpret the incoming data, improving data handling in industrial automation systems. The system enhances interoperability and reduces errors in data transmission within process control environments.
2. The system according to claim 1 , wherein the description of the format of the data stream that is included in the set of metadata includes a respective identifier assigned by the first device to each of one or more respective instances of a respective function block, a respective control module, a respective parameter, a respective unit corresponding to the first device, a respective other device that accesses or acts on the at least one of the process input or the process output of the first device, a respective event, or a respective alarm.
3. The system according to claim 1 , wherein the respective descriptions of the types of data included in the data stream that are included in the set of metadata include a respective identifier assigned by a user to each of one or more of: a respective function block, a respective control module, a respective parameter, a respective unit corresponding to the first device, a respective other device that accesses or acts on the at least one of the process input or the process output of the first device, a respective event, or a respective alarm.
4. The system according to claim 1 , wherein the second device that is operable to receive the data stream comprises a big data appliance.
5. The system according to claim 1 , wherein the first device automatically updates the set of metadata based on a change to the configuration of the first device.
6. The system according to claim 1 , wherein: the second device that is operable to receive the data stream is further configured to: identify, in the data stream, an identifier that is not in the set of metadata, wherein the set of metadata is a first set of metadata, cache the data stream, and send a request to the first device that is operable to send the data stream to provide an updated set of metadata; the first device is further configured to: receive the request to provide the updated set of metadata, and send the updated set of metadata to the second device; and the second device is still further configured to: receive the updated set of metadata and parse the cached data stream according to the updated set of metadata.
7. The system according to claim 1 , wherein: the first device that is operable to transmit the data stream is further configured to: recognize a configuration change, update the set of metadata according to the recognized configuration change, and send the updated set of metadata to the second device that is operable to receive the data stream; and the second is further configured to: receive the updated set of metadata, receive, from the first device, the data stream, wherein the data stream is structured according to the updated set of metadata, and parse the data stream according to the updated set of metadata.
8. The system according to claim 1 , wherein the system is further configured to perform an analysis on the set of data to generate analysis data.
9. The system according to claim 8 , wherein the analysis is performed at the first device that is operable to transmit the data stream, and wherein the analysis data are added to the data stream.
This invention relates to a system for analyzing and transmitting data streams, particularly in environments where real-time processing and data augmentation are required. The system addresses the challenge of efficiently analyzing data at the source device before transmission, reducing latency and bandwidth usage by embedding analysis results directly into the data stream. The system includes a first device capable of generating or receiving a data stream, such as sensor data, video, or network traffic. This device performs an analysis on the data stream, which may involve detecting patterns, anomalies, or specific features within the data. The analysis results, referred to as analysis data, are then added to the data stream itself, either as metadata or embedded within the data payload. This allows downstream devices or systems to access the analysis data without requiring separate processing or additional transmissions. The system ensures that the analysis is conducted at the first device, minimizing delays and ensuring that the data stream remains self-contained with its derived insights. This approach is particularly useful in applications like IoT networks, industrial monitoring, or real-time analytics, where immediate feedback and reduced latency are critical. By integrating analysis data into the data stream, the system optimizes resource usage and improves efficiency in data processing workflows.
10. The system according to claim 1 , wherein the data stream comprises a timestamp.
A system for processing data streams includes a mechanism to analyze and manage incoming data, where the data stream contains a timestamp. The timestamp allows for precise tracking of when each data entry was generated or received, enabling time-based filtering, synchronization, or ordering of data. This feature is particularly useful in applications requiring temporal accuracy, such as real-time monitoring, event logging, or time-series analysis. The system may further include components for validating, transforming, or routing the data based on the timestamp, ensuring that time-sensitive operations are executed correctly. By incorporating timestamps, the system enhances data integrity and enables more sophisticated time-based analytics, such as trend detection or anomaly identification. The timestamp may be embedded within the data stream itself or added during ingestion, depending on the system's configuration. This approach ensures that time-related metadata is consistently available for downstream processing, improving reliability and usability in time-critical applications.
11. The system according to claim 10 , wherein the data stream comprises a plurality of incremental timestamps, each incremental timestamp associated with a sub-set of data in the set of data.
12. The system according to claim 1 , wherein the data stream comprises a plurality of identifiers defined by the set of metadata, and respective data corresponding to each identifier included in the plurality of identifiers.
13. A method of streaming data in a process control system of a process plant, the method comprising: storing a set of metadata in a first device that is (a) operable, during run-time of the process plant, to transmit a data stream, (b) included in the process control system, and (c) further operable, during run-time of the process plant, to control a process in the process plant to thereby generate a physical material or product, the first device being one of (i) a controller communicatively connected to one or more field devices disposed in the process plant, the controller configured to send control signals to the one or more field devices to thereby control the process during run-time in the process plant, or (ii) one of the one or more field devices, and the set of metadata comprising (i) respective descriptions of types of data included in the data stream and (ii) a description of a format of the data stream, and including respective identifiers of one or more portions of a configuration of the first device, the one or more portions of the configuration of the first device including at least one of: a control module that is downloaded into the controller and executable during run-time to generate and send the control signals to the one or more field devices to thereby control the process in the process plant, a function block included in the control module, a process parameter, a unit corresponding to the first device, another device that accesses or acts on at least one of a process input or a process output of the first device, an event, or an alarm; collecting a set of data for transmitting as the data stream, the set of data generated by the first device and including a set of values of one more parameters whose respective values vary as a result of the first device operating to control the process; buffering the set of collected data; transmitting, all of the set of metadata to a second device that is operable to receive the data stream, prior to transmitting the data stream to the second device; and subsequent to transmitting the set of metadata to the second device, transmitting the data stream to the second device, wherein no further metadata are transmitted to the second device unless a trigger event causes the first device to transmit additional metadata.
This invention relates to streaming data in a process control system for a process plant, where the system controls physical processes to produce materials or products. The challenge addressed is efficiently transmitting and interpreting data streams from control devices in real-time while minimizing unnecessary metadata overhead. The method involves a first device, which can be either a controller or a field device, that controls a process in the plant. The first device stores metadata describing the data stream, including data types, stream format, and identifiers for configuration elements such as control modules, function blocks, process parameters, units, related devices, events, or alarms. During operation, the first device collects process data, buffers it, and transmits the metadata to a second receiving device before sending the actual data stream. Additional metadata is only sent if a trigger event occurs, ensuring efficient communication. This approach ensures that the receiving device understands the structure and context of the data stream before processing it, reducing errors and improving real-time monitoring and control in industrial environments. The method optimizes bandwidth by transmitting metadata only when necessary, enhancing system performance.
14. The method according to claim 13 , further comprising: receiving, from the second device, a request for updated metadata; generating or downloading the updated metadata; and sending the updated metadata to the second device in response to the request for updated metadata.
15. The method according to claim 13 , further comprising: recognizing a changed configuration parameter; generating or downloading updated metadata corresponding to the changed configuration parameter; and sending the updated metadata to the second device before sending a data stream according to the updated metadata.
16. The method according to claim 13 , wherein the description of the format of the data stream that is included in the set of metadata includes a respective identifier assigned by the first device to each of one or more respective instances of a respective function block, a respective control module, a respective parameter, a respective unit corresponding to the first device, a respective other device that accesses or acts on the at least one of the process input or the process output of the first device, a respective event, or a respective alarm.
This invention relates to industrial automation systems, specifically improving data stream management and interoperability between devices. The problem addressed is the lack of standardized metadata in industrial communication protocols, which complicates integration and troubleshooting across heterogeneous systems. The method involves generating metadata that describes the format of a data stream exchanged between devices in an industrial process control system. This metadata includes identifiers assigned by a first device to various system components, such as function blocks, control modules, parameters, units, other devices interacting with the first device, events, and alarms. These identifiers uniquely reference specific instances of these components, enabling precise tracking and management of data streams. The metadata is structured to facilitate interoperability, allowing other devices to accurately interpret the data stream's format and content. This approach enhances system integration, diagnostics, and maintenance by providing clear, standardized references to system elements involved in data exchange. The solution is particularly useful in complex industrial environments where multiple devices from different vendors must communicate seamlessly.
17. The method according to claim 13 , wherein respective descriptions of the types of data included in the data stream that are included in the set of metadata include a respective identifier assigned by a user to each of one or more of: a respective function block, a respective control module, a respective parameter, a respective unit corresponding to the first device, a respective other device that accesses or acts on the at least one of the process input or the process output of the first device, a respective event, or a respective alarm.
18. The method according to claim 13 , wherein the second device comprises a big data appliance.
A system and method for processing large-scale data involves a distributed computing framework that integrates a big data appliance as a second device to enhance data processing capabilities. The big data appliance is configured to handle high-volume, high-velocity data streams, enabling real-time or near-real-time analytics. The system includes a first device that collects and preprocesses data before transmitting it to the big data appliance for further analysis. The big data appliance employs parallel processing techniques to distribute workloads across multiple nodes, improving efficiency and scalability. The system also includes a data storage component that stores processed data for future retrieval and analysis. The integration of the big data appliance allows the system to manage complex data operations, such as machine learning, predictive modeling, and large-scale data aggregation, which are critical for applications in fields like finance, healthcare, and telecommunications. The method ensures seamless data flow between the first device and the big data appliance, optimizing resource utilization and reducing processing latency. This approach addresses the challenge of handling massive datasets by leveraging distributed computing and specialized hardware to achieve faster, more accurate insights.
19. The method according to claim 13 , further comprising performing an analysis on the set of data to generate analysis data.
20. The method according to claim 19 , further comprising adding the analysis data to the data stream.
21. The method according to claim 13 , wherein the data stream comprises a timestamp.
22. The method according to claim 21 , wherein the data stream comprises a plurality of incremental timestamps, each incremental timestamp associated with a sub-set of data in the set of data.
The invention relates to data processing systems that handle time-stamped data streams, particularly for applications requiring efficient storage, retrieval, or analysis of time-series data. A common challenge in such systems is managing large datasets where data is continuously generated or updated, making it difficult to track changes or access specific subsets of data efficiently. The invention addresses this problem by introducing a method for processing a data stream that includes a plurality of incremental timestamps. Each incremental timestamp is associated with a subset of data within a larger dataset. This approach allows for granular tracking of data changes over time, enabling efficient updates, queries, and analysis. The method ensures that only relevant subsets of data are processed or retrieved based on their associated timestamps, reducing computational overhead and improving performance. The data stream may be part of a larger system that processes time-series data, such as financial transactions, sensor readings, or log files. By associating incremental timestamps with specific subsets of data, the system can quickly identify and access the most recent or relevant portions of the dataset without scanning the entire collection. This is particularly useful in real-time applications where low latency and high efficiency are critical. The method may also include additional features, such as compressing or encrypting the data subsets to further optimize storage and security. The timestamps can be used to reconstruct the dataset at any point in time, enabling historical analysis or rollback capabilities. Overall, the invention provides a scalable and efficient way to manage time-stamped data streams in various computing environments.
23. The method according to claim 13 , wherein the data stream comprises a plurality of identifiers defined by the set of metadata, and respective data corresponding to each identifier included in the plurality of identifiers.
This invention relates to data processing systems that handle data streams containing multiple identifiers and associated data. The problem addressed is efficiently managing and processing such data streams, particularly when the identifiers and their corresponding data are dynamically defined by metadata. The invention provides a method for processing a data stream where the stream includes a plurality of identifiers, each defined by a set of metadata, and respective data corresponding to each identifier. The method involves analyzing the metadata to determine the structure and relationships of the identifiers and their associated data, enabling efficient storage, retrieval, and manipulation of the data. The system dynamically adapts to changes in the metadata, ensuring that the data stream remains consistent and accurately processed. This approach is particularly useful in applications where data streams are complex, such as in real-time analytics, database management, or distributed computing environments. The method ensures that the data stream is processed in a way that maintains the integrity and accessibility of the data, even as the metadata evolves. The invention improves upon prior systems by providing a more flexible and scalable solution for handling dynamically defined data structures.
24. A method for receiving a data stream in a process control system of a process plant, the method comprising: receiving a set of metadata from a first device that is included in the process control system, and that is operable, during run-time of the process plant, to transmit the data stream and to control a process in the process plant to thereby generate a physical material or product, the first device being one of (i) a controller communicatively connected to one or more field devices disposed in the process plant, the controller configured to send control signals to the one or more field devices to thereby control the process during run-time in the process plant, or (ii) one of the one or more field devices, and the set of metadata comprising (i) respective descriptions of types of data included in the data stream and (ii) a description of a format of the data stream, and including respective identifiers of one or more portions of a configuration of the first device, the one or more portions of the configuration of the first device including at least one of: a control module that is downloaded into the controller and executable during run-time to generate and send the control signals to the one or more field devices to thereby control the process in the process plant, a function block included in the control module, a process parameter, a unit corresponding to the first device, another device that accesses or acts on at least one of a process input or a process output of the first device, an event, or an alarm; receiving the data stream from the first device after receiving all of the set of metadata, the data stream including a set of data generated by the first device, and the set of data including a set of values of one or more parameters whose respective values vary as a result of the first device operating to control the process; parsing the received data stream according to the set of metadata; and continuing to receive streamed data from the first device as long as the data stream can be parsed according to the set of metadata.
25. The method according to claim 24 , further comprising: identifying, in the data stream, an identifier that cannot be parsed according to the set of metadata; caching the data stream; sending a request, to the first device that is operable to transmit the data stream, to provide updated metadata; receiving the updated metadata; parsing the cached data stream according to the updated metadata; continuing to receive the data stream; and parsing the data stream according to the updated metadata.
This invention relates to data stream processing systems that handle metadata parsing and updates. The problem addressed is the inability to parse data streams when metadata is incomplete or outdated, leading to processing interruptions. The system includes a device that receives a data stream from a transmitting device, where the data stream is structured according to metadata. The system initially parses the data stream using a set of metadata but may encounter an identifier that cannot be parsed due to missing or incorrect metadata. In response, the system caches the data stream, sends a request to the transmitting device for updated metadata, and receives the updated metadata. The cached data stream is then parsed using the updated metadata, and subsequent data streams are parsed according to the updated metadata. This ensures continuous data processing without interruptions caused by metadata discrepancies. The system may also include a metadata repository that stores metadata for multiple data streams and devices, allowing for efficient retrieval and updates. The invention improves data stream processing reliability by dynamically adapting to metadata changes.
26. The method according to claim 24 , further comprising: receiving updated metadata from the first device; continuing to receive the data stream from the first device; and parsing the data stream according to the updated metadata, wherein the data stream received after the updated metadata is able to be parsed according to the updated metadata, and is not able to be parsed according to the set of metadata.
This invention relates to systems for processing data streams with dynamic metadata updates. The problem addressed is the need to handle data streams where the metadata structure changes over time, requiring real-time adaptation to ensure accurate parsing and interpretation of the data. The method involves a system that initially receives a data stream from a first device, where the data is structured according to a predefined set of metadata. The system parses the incoming data stream based on this initial metadata. However, the system is also capable of receiving updated metadata from the first device, which may modify the structure or format of the data stream. Upon receiving the updated metadata, the system continues to receive the data stream but adjusts its parsing logic to align with the new metadata. The data received after the metadata update can only be parsed correctly using the updated metadata, as it no longer conforms to the original metadata structure. This ensures that the system remains synchronized with the evolving data stream, preventing parsing errors or data loss due to metadata changes. The method is particularly useful in environments where data streams are dynamic, such as IoT devices, sensor networks, or real-time analytics systems.
27. The method according to claim 24 , wherein the description of the format of the data stream that is included in the set of metadata includes a respective identifier assigned by the first device to each of one or more respective instances of a respective function block, a respective control module, a respective parameter, a respective unit corresponding to the first device, a respective other device that accesses or acts on the at least one of the process input or the process output of the first device, a respective event, or a respective alarm.
28. The method according to claim 24 , wherein respective descriptions of the types of data included in the data stream that are included in the set of metadata include a respective identifier assigned by a user to each of one or more of: a respective function block, a respective control module, a respective parameter, a respective unit corresponding to the first device, a respective other device that accesses or acts on the at least one of the process input or the process output of the first device, a respective event, or a respective alarm.
29. The method according to claim 24 , wherein the method is performed by a second device comprising a big data appliance.
30. The method according to claim 24 , further comprising performing an analysis on the set of data to generate analysis data.
31. The method according to claim 30 , wherein the analysis data are stored in a big data appliance.
32. The method according to claim 24 , wherein the data stream comprises a timestamp.
A system and method for processing data streams in real-time applications, particularly in environments requiring precise time synchronization. The invention addresses the challenge of accurately tracking and analyzing data events in systems where timing information is critical, such as financial transactions, industrial monitoring, or network communications. The method involves capturing a data stream containing event data and associating each event with a timestamp to ensure chronological accuracy. The timestamp enables time-based filtering, correlation, and analysis of events, allowing for improved synchronization and event reconstruction. The system may further include mechanisms for validating timestamps, handling time discrepancies, and integrating with external time sources to enhance reliability. By embedding timestamps within the data stream, the invention ensures that events are processed in the correct temporal order, reducing errors in time-sensitive applications. The method may also support dynamic adjustments to timestamp resolution based on system requirements, optimizing performance without sacrificing accuracy. This approach enhances the reliability of time-dependent operations in distributed systems, ensuring consistent and precise event sequencing.
33. The method according to claim 32 , wherein the data stream comprises a plurality of incremental timestamps, each incremental timestamp associated with a sub-set of data in the set of data.
This invention relates to data processing systems that handle time-stamped data streams. The problem addressed is efficiently managing and analyzing large datasets where data is received incrementally over time, requiring precise tracking of when each subset of data was generated or processed. The method processes a data stream containing multiple incremental timestamps, each linked to a specific subset of data within a larger dataset. These timestamps allow the system to track the chronological order of data subsets, enabling accurate time-based analysis, synchronization, or reconstruction of the full dataset. The method ensures that each subset is associated with its correct timestamp, maintaining data integrity and temporal coherence. The system may also include mechanisms to validate, adjust, or interpolate timestamps if discrepancies are detected, ensuring reliable time-based operations. This approach is particularly useful in applications like financial transactions, sensor data logging, or distributed computing, where maintaining the temporal sequence of data is critical. The method can be integrated into larger data processing workflows, such as real-time analytics, event-driven systems, or historical data reconstruction, where precise time tracking enhances accuracy and usability. By associating timestamps with specific data subsets, the system ensures that time-sensitive operations remain consistent and reliable.
34. The method according to claim 24 , wherein the data stream comprises a plurality of identifiers defined by the set of metadata, and respective data corresponding to each identifier included in the plurality identifiers.
35. An apparatus in a process control system of a process plant, the apparatus comprising: a processor; a data source providing data to the apparatus, the data source included in the process control system and operable, during a run-time of the process plant, to control a process in the process plant to thereby generate a physical material or product, the data generated by the data source including a set of values of one or more parameters whose respective values vary as a result of the data source operating to control the process, and the apparatus being one of (i) a controller communicatively connected to one or more field devices disposed in the process plant, the controller configured to send control signals to the one or more field devices to thereby control the process during run-time in the process plant, or (ii) one of the one or more field devices; a memory communicatively coupled to the processor and storing a set of metadata, the set of metadata comprising (i) respective descriptions of types of the data and (ii) a description of a format of the data, and including respective identifiers of one or more portions of a configuration of the apparatus, the one or more portions of the configuration of the apparatus including at least one of: a control module that is downloaded into the controller and executable during run-time to generate and send the control signals to the one or more field devices to thereby control the process in the process plant, a function block included in the control module, a process parameter, a unit corresponding to the first device, another device that accesses or acts on at least one of a process input or a process output of the first device, an event, or an alarm; a queuing routine executing on the processor to buffer data received from the data source; and a data streaming routine executing on the processor and cooperating with a communication device to: transmit all of the stored set of metadata to a receiving device prior to transmitting the data stream to the receiving device; assemble the buffered data into a data stream according to the stored set of metadata; and transmit the data stream to the receiving device.
36. The apparatus according to claim 35 , wherein the apparatus is the controller, the data source comprises one or more process control devices whose generated data is received at an input of the controller, and the apparatus further comprises: one or more routines executing on the processor to control the process according at least in part based on the received data; and a collection routine executing on the processor and collecting the data received from the one or more process control devices.
This invention relates to a controller apparatus for process control systems, addressing the need for efficient data collection and process management in industrial automation. The apparatus includes a processor and a data source, which consists of one or more process control devices that generate operational data. This data is received at an input of the controller. The apparatus further includes routines executing on the processor to control the process based on the received data, ensuring real-time adjustments and optimization. Additionally, a dedicated collection routine runs on the processor to gather and manage the data from the process control devices, enabling centralized monitoring and analysis. The controller integrates these functions to enhance process efficiency, reliability, and responsiveness in industrial environments. The system ensures seamless data flow and control, improving overall system performance by leveraging the collected data for decision-making and process adjustments. This approach streamlines operations, reduces manual intervention, and supports predictive maintenance and automation in process control applications.
37. The apparatus according to claim 35 , wherein the data streaming routine executing on the processor is further operable to: receive a request for updated metadata; generate or download updated metadata; and send the updated metadata in response to the request for updated metadata.
38. The apparatus according to claim 35 , further comprising a metadata updating routine operable to receive or generate updated metadata, and wherein the data streaming routine executing on the processor is further operable to: send updated metadata in response to a detected change in the configuration of the apparatus or in response to the generation or reception of updated metadata; and continue sending the data stream, wherein the data stream sent after the updated metadata are sent is structured according to the updated metadata.
This invention relates to a data streaming apparatus that dynamically updates metadata while maintaining continuous data transmission. The apparatus includes a processor executing a data streaming routine to send a data stream structured according to metadata, which defines the format, structure, or properties of the data. A metadata updating routine receives or generates updated metadata, triggering the apparatus to send the updated metadata in response to configuration changes or new metadata. The data streaming routine then continues sending the data stream, now structured according to the updated metadata, ensuring seamless adaptation without interrupting the stream. This allows real-time adjustments to data transmission parameters, such as format, encoding, or protocol, while preserving continuity. The invention addresses the challenge of maintaining uninterrupted data flow during metadata updates, which is critical in applications like live broadcasting, IoT sensor networks, or real-time analytics where metadata changes may be necessary due to dynamic conditions or user requirements. The apparatus ensures that recipients of the data stream can process the updated metadata and adapt to the new structure without losing data or experiencing disruptions.
39. The apparatus according to claim 35 , wherein the description of the format of the data stream that is included in the set of metadata includes a respective identifier assigned by the data source or the apparatus to each of one or more respective instances of a respective function block, a respective control module, a respective parameter, a respective unit corresponding to the first device, a respective other device that accesses or acts on the at least one of the process input or the process output of the first device, a respective event, or a respective alarm.
40. The apparatus according to claim 35 , wherein the respective descriptions of the types of data included in the data stream that are included in the set of metadata include a respective identifier assigned by a user to each of one or more of: a respective function block, a respective control module, a respective parameter, a respective unit corresponding to the first device, a respective other device that accesses or acts on the at least one of the process input or the process output of the first device, a respective event, or a respective alarm.
41. The apparatus according to claim 35 , wherein the receiving device comprises a big data appliance.
A system for processing and analyzing large-scale data streams is disclosed. The system addresses the challenge of efficiently handling and extracting insights from high-volume, high-velocity data in real-time or near-real-time environments. The apparatus includes a receiving device configured to capture and process incoming data streams, which may originate from multiple sources such as sensors, logs, or transactional systems. The receiving device is designed to handle big data workloads, leveraging a big data appliance that integrates distributed computing, storage, and analytics capabilities. This appliance may include components such as distributed file systems, parallel processing frameworks, and in-memory databases to ensure scalability and performance. The system further includes a processing module that applies predefined rules, algorithms, or machine learning models to the incoming data, enabling real-time filtering, aggregation, or predictive analysis. The processed data may then be stored, visualized, or transmitted to downstream applications for further use. The apparatus ensures fault tolerance, load balancing, and dynamic resource allocation to maintain reliability and efficiency under varying data loads. The solution is particularly useful in industries such as finance, healthcare, and telecommunications, where timely data processing is critical for decision-making.
42. The apparatus according to claim 35 , further comprising an analysis routine executing on the processor to analyze the received data to generate analysis data.
43. The apparatus according to claim 42 , wherein the data streaming routine executing on the processor is further operable to add the analysis data to the data stream.
This invention relates to data processing systems, specifically apparatuses for analyzing and streaming data. The problem addressed is the need to efficiently integrate analysis data into a continuous data stream without disrupting the flow or requiring separate processing steps. The apparatus includes a processor executing a data streaming routine that processes a data stream in real-time. The routine performs analysis on the incoming data, such as statistical calculations, pattern recognition, or other computational tasks. The key improvement is that the same routine responsible for streaming the data also appends the generated analysis data directly to the data stream. This eliminates the need for additional processing steps or external systems to merge the analysis results with the original data. The apparatus may include input interfaces to receive the data stream from various sources, such as sensors, databases, or network feeds. The processor executes the streaming routine, which processes the data sequentially, ensuring low-latency operation. The analysis data, once generated, is inserted into the data stream in a structured format, such as metadata tags or separate data packets, allowing downstream systems to access both the original and analyzed data seamlessly. This approach improves efficiency by reducing the overhead of separate analysis and streaming processes, making it suitable for applications requiring real-time data processing, such as IoT systems, financial trading platforms, or industrial monitoring. The integration of analysis within the streaming routine ensures that the data remains coherent and synchronized, enhancing reliability and usability.
44. The apparatus according to claim 35 , wherein the data stream comprises a timestamp.
45. The apparatus according to claim 44 , wherein the data stream comprises a plurality of incremental timestamps, each incremental timestamp associated with a sub-set of data in the data.
46. The apparatus according to claim 35 , wherein the data stream comprises a plurality of identifiers defined by the set of metadata, and respective data corresponding to each identifier included in the plurality of identifiers.
47. An apparatus for receiving a stream of big data in a process control system of a process plant, the apparatus comprising: a processor; a memory communicatively coupled to the processor; a non-transitory memory device; and a receiver operable to: receive a set of metadata, the set of metadata comprising (i) respective descriptions of types of data included in a data stream and (ii) a description of a format of the data stream, and including respective identifiers of one or more portions of a configuration of the particular device, the one or more portions of the configuration of the particular device including at least one of: a control module that is downloaded into the controller and executable during run-time to generate and send the control signals to the one or more field devices to thereby control the process in the process plant, a function block included in the control module, a process parameter, a unit corresponding to the first device, another device that accesses or acts on at least one of a process input or a process output of the first device, an event, or an alarm; receive the data stream after receiving all of the set of metadata, the data stream including data generated by a particular device that is included in the process control system and that is operable, during run-time of the process plant, to control a process in the process plant to thereby generate a physical material or product, the particular device being one of (i) a controller communicatively connected to one or more field devices disposed in the process plant, the controller configured to send control signals to the one or more field devices to thereby control the process during run-time in the process plant, or (ii) one of the one or more field devices, and the data generated by the particular device including a set of values of one or more parameters whose respective values vary as a result of the particular device operating to control the process; parse the data stream according to the set of metadata; process the data included in the data stream according to the parsing; and continue to receive and process data as long as the data stream can be parsed according to the set of metadata.
48. The apparatus according to claim 47 , wherein the apparatus is a big data appliance for storing big data, wherein the non-transitory memory device comprises a high fidelity data storage device, and wherein processing data comprises storing the data in the high fidelity data storage device.
This invention relates to a big data appliance designed for efficient storage and processing of large-scale data. The apparatus includes a non-transitory memory device configured as a high fidelity data storage system, optimized for handling big data workloads. The high fidelity storage ensures data integrity, reliability, and performance, addressing challenges associated with storing and retrieving massive datasets. The apparatus processes data by storing it in the high fidelity storage device, which may involve techniques such as deduplication, compression, or distributed storage to enhance efficiency. The system is particularly suited for environments requiring high availability, scalability, and fault tolerance, such as data centers, cloud computing platforms, or enterprise storage solutions. By integrating high fidelity storage, the apparatus mitigates risks of data corruption, loss, or performance degradation, which are common in traditional big data storage systems. The invention improves data management by leveraging advanced storage technologies to support large-scale analytics, machine learning, or real-time processing applications. The apparatus may also include additional components, such as processors, network interfaces, or caching mechanisms, to further optimize data handling and retrieval operations.
49. The apparatus according to claim 47 , wherein the receiver is further operable to: identify in the data stream an identification that cannot be parsed according to the set of metadata; cache the data stream; send a request to provide updated metadata; receive the updated metadata; parse the cached data stream according to the updated metadata; process the data included in the cached data stream according to the parsing; continue to receive the data stream; parse the continued data stream according to the updated metadata; and process the data from the continued data stream.
50. The apparatus according to claim 47 , wherein the receiver is further operable to: receive updated metadata; continue to receive the data stream; and parse the continued data stream according to the updated metadata, wherein the data stream received after the updated metadata is able to be parsed according to the updated metadata, and is not able to be parsed according to the set of metadata.
51. The apparatus according to claim 47 , wherein the description of the format of the data stream that is included in the set of metadata includes a respective identifier assigned by the first device to each of one or more respective instances of a respective function block, a respective control module, a respective parameter, a respective unit corresponding to the first device, a respective other device that accesses or acts on the at least one of the process input or the process output of the first device, a respective event, or a respective alarm.
This invention relates to industrial automation systems, specifically to apparatuses that manage data streams between devices in a process control system. The problem addressed is the lack of standardized metadata in data streams, which complicates interoperability and integration between different devices and systems. The apparatus includes a first device configured to generate a data stream representing at least one of a process input or a process output. The apparatus also includes a second device configured to receive and process the data stream. The first device includes a metadata generator that creates a set of metadata describing the format of the data stream. This metadata includes identifiers assigned by the first device to various components, such as function blocks, control modules, parameters, units corresponding to the first device, other devices interacting with the first device, events, or alarms. These identifiers ensure that the data stream is properly interpreted by the second device, enabling seamless communication and coordination between devices in the process control system. The metadata may also include additional information such as data types, units of measurement, and relationships between different data elements. This structured approach to metadata improves system reliability, reduces integration errors, and enhances overall efficiency in industrial automation environments.
52. The apparatus according to claim 47 , wherein respective descriptions of the types of data included in the data stream that are included in the set of metadata include a respective identifier assigned by a user to each of one or more of: a respective function block, a respective control module, a respective parameter, a respective unit corresponding to the first device, a respective other device that accesses or acts on the at least one of the process input or the process output of the first device, a respective event, or a respective alarm.
53. The apparatus according to claim 47 , wherein the apparatus is operable to stream big data to a downstream device.
This invention relates to an apparatus for processing and transmitting large-scale data, addressing the challenge of efficiently handling and distributing big data in real-time applications. The apparatus is designed to receive, process, and stream big data to downstream devices, ensuring seamless data flow and minimizing latency. It includes components for data ingestion, preprocessing, and real-time analysis, enabling the apparatus to manage high-volume, high-velocity data streams. The apparatus may also incorporate data compression, encryption, or protocol optimization techniques to enhance transmission efficiency and security. By streaming big data to downstream devices, the apparatus supports applications such as real-time analytics, IoT data processing, and large-scale distributed computing. The invention improves data accessibility and reduces bottlenecks in data-intensive systems.
54. The apparatus according to claim 47 , further comprising an analysis module operable to perform an analysis on the data included in the data stream to generate analysis data.
This invention relates to data processing systems, specifically apparatuses for handling and analyzing data streams. The problem addressed is the need for efficient and flexible analysis of real-time or high-volume data streams, which often require processing without disrupting the flow of data. The apparatus includes a data stream receiver that captures incoming data streams from one or more sources. A data stream processor then processes the data, which may involve filtering, formatting, or transforming the data to prepare it for further analysis. The processed data is stored in a data storage module, which maintains the data in a structured format for quick retrieval and analysis. An analysis module performs an analysis on the stored data to generate analysis data. This analysis could include statistical computations, pattern recognition, anomaly detection, or other forms of data interpretation. The analysis results are then made available for further use, such as decision-making, reporting, or triggering automated actions. The apparatus is designed to handle continuous or batch data streams, ensuring that the analysis is performed efficiently without causing delays in data processing. The modular design allows for customization, enabling different types of data streams and analysis techniques to be integrated as needed. This system is particularly useful in applications like real-time monitoring, fraud detection, or predictive analytics where timely and accurate data processing is critical.
55. The apparatus according to claim 54 , wherein the analysis data are stored in the non-transitory memory device.
56. The apparatus according to claim 47 , wherein the data stream comprises a timestamp.
57. The apparatus according to claim 56 , wherein the data stream comprises a plurality of incremental timestamps, each incremental timestamp associated with a sub-set of data in the data stream.
58. The apparatus according to claim 47 , wherein the data stream comprises a plurality of identifiers defined by the set of metadata, and respective data corresponding to each identifier included in the plurality of identifiers.
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February 2, 2021
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